Create README.md

README.md

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+---
+tags:
+- structured-data-classification
+dataset:
+- wine-quality
+library_name: scikit-learn
+---
+
+## Wine Quality classification
+
+### A Simple Example of Scikit-learn Pipeline
+
+> Inspired by https://towardsdatascience.com/a-simple-example-of-pipeline-in-machine-learning-with-scikit-learn-e726ffbb6976
+
+
+### How to use
+
+```python
+from huggingface_hub import hf_hub_url, cached_download
+import joblib
+import pandas as pd
+
+REPO_ID = "julien-c/wine-quality"
+FILENAME = "sklearn_model.joblib"
+
+
+model = joblib.load(cached_download(
+    hf_hub_url(REPO_ID, FILENAME)
+))
+
+# model is a `sklearn.pipeline.Pipeline`
+
+data_file = cached_download(
+    hf_hub_url(REPO_ID, "winequality-red.csv")
+)
+winedf = pd.read_csv(data_file, sep=";")
+
+
+X = winedf.drop(["quality"], axis=1)
+Y = winedf["quality"]
+
+
+labels = model.predict(X[:3])
+```
+
+^^ get your prediction
+
+#### Eval
+
+```python
+model.score(X, Y)
+# 0.6616635397123202
+```
+
+### 🍷 Disclaimer
+
+No red wine was drunk (unfortunately) while training this model 🍷
+